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Related Experiment Video

Updated: Jun 27, 2026

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A Joint-Level Hybrid Framework for Gait Analysis Using Camera-IMU Fusion and LSTM-Based Temporal Correction.

Eunju Ha1, Jong-Wook Kim1

  • 1Department of Electronic Engineering, Seunghak Campus, Dong-A University, Busan 49315, Republic of Korea.

Sensors (Basel, Switzerland)
|June 26, 2026
PubMed
Summary

This study introduces a hybrid gait analysis system using one camera and two inertial measurement units (IMUs). The framework accurately estimates lower limb joint angles, offering a practical solution for portable gait analysis.

Keywords:
LSTMRGB cameragait analysisinertial measurement unitjoint angle estimationsensor fusion

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FIM Imaging and FIMtrack: Two New Tools Allowing High-throughput and Cost Effective Locomotion Analysis
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Published on: December 24, 2014

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Last Updated: Jun 27, 2026

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FIM Imaging and FIMtrack: Two New Tools Allowing High-throughput and Cost Effective Locomotion Analysis

Published on: December 24, 2014

Area of Science:

  • Biomechanics
  • Human Movement Analysis
  • Wearable Technology

Background:

  • Marker-based motion capture is costly and spatially restrictive.
  • Accurate gait analysis is crucial for diagnosing musculoskeletal disorders and rehabilitation.
  • Existing markerless systems face challenges in precision and portability.

Purpose of the Study:

  • To develop and validate a hybrid framework for joint-level gait analysis using a single RGB camera and two shoe-mounted inertial measurement units (IMUs).
  • To overcome the limitations of traditional marker-based systems by integrating complementary sensor strengths.
  • To provide a practical and interpretable approach for portable lower limb gait analysis.

Main Methods:

  • A hybrid framework combining a single RGB camera for hip and knee sagittal angle estimation (using 3D pose estimation, DEAS optimization, and LSTM refinement) and two IMUs for ankle angle estimation.
  • Utilized kinematic chain relationships, integrating camera-derived proximal joint data with IMU-measured foot orientation.
  • Employed leave-one-subject-out (LOSO) cross-validation for the LSTM correction model to assess generalizability.

Main Results:

  • Achieved promising estimation performance with an average Mean Absolute Error (MAE) of 7.89° and Root Mean Square Error (RMSE) of 10.09° for sagittal hip, knee, and ankle angles on a held-out test set.
  • LOSO cross-validation of the LSTM correction model demonstrated generalizability, yielding an average MAE of 6.40° for bilateral hip angles.
  • Successfully mitigated trunk-inclination-induced overestimation of hip angles.

Conclusions:

  • The proposed hybrid framework offers a practical and interpretable solution for portable lower limb gait analysis.
  • The integration of a single camera and two IMUs provides accurate joint-level angle estimations.
  • This approach overcomes the cost and spatial limitations of traditional marker-based systems, enhancing clinical applicability.